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2025 Vol.19, Issue 5 Preview Page

Research Article

Causal Effect of Enhanced Insulation Levels on Heating Energy Consumption in South Korean Apartments

인과추론 기반 국내 아파트 단열 강화의 난방에너지 절감 효과 분석

Young-Seo Yoo1
,
Cheol-Soo Park2
,
Deuk-Woo Kim3
,
Ki-Uhn Ahn4*
유 영서1
,
박 철수2
,
김 덕우3
,
안 기언4*
1Post-doctoral Researcher, Department of Building Research, Korea Institute of Civil Engineering and Building Technology, Goyang, Korea
2Professor, Department of Architecture and Architectural Engineering, Seoul National University, Seoul, Korea
3Senior Researcher, Department of Building Energy Research, Korea Institute of Civil Engineering and Building Technology, Goyang, Korea
4Senior Researcher, Department of Building Research, Korea Institute of Civil Engineering and Building Technology, Goyang, Korea
1한국건설기술연구원 건축연구본부 박사후연구원
2서울대학교 건축학과 교수
3한국건설기술연구원 건축에너지연구본부 수석연구원
4한국건설기술연구원 건축연구본부 수석연구원
*Corresponding Author
30 October 2025. pp. 212-222
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Abstract

The Korean government has continuously reinforced insulation standards in residential buildings to reduce heating energy consumption. This study applies causal inference to evaluate their effectiveness, estimating the “pure effect” of insulation improvements by isolating the influence of other factors. A dataset of 1,313 apartment buildings was selected by linking the national building register, meteorological data, and energy consumption data. Insulation level was defined as the treatment variable representing the policy intervention, while heating energy use intensity (EUI) served as the outcome. Heating degree days and apartment sale prices were incorporated as confounders, as they affect both insulation levels and heating EUI. The CausalForestDML method was applied to estimate both average treatment effects (ATE) and conditional average treatment effects (CATE). Results show that correlation-based approaches tend to overstate energy savings, whereas causal inference provides more moderate and reliable estimates after accounting for climatic and socioeconomic factors. Furthermore, the effectiveness of insulation improvements varied by baseline thermal performance, regional climate conditions, and socioeconomic characteristics, indicating substantial heterogeneity in policy impacts. These findings highlight the value of causal inference as a rigorous framework for policy evaluation, enabling more objective assessment and supporting the design of effective, targeted energy-saving strategies.

Keywords
Building energy analysis
Insulation improvement effects
Correlation analysis
Causal inference
CausalforestDML
키워드
건물 에너지 분석
단열 강화 효과
상관분석
인과추론
인과 포레스트 기법
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Information
  • Publisher :Korean Institute of Architectural Sustainable Environment and Building Systems
  • Publisher(Ko) :한국건축친환경설비학회
  • Journal Title :Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
  • Journal Title(Ko) :한국건축친환경설비학회논문집
  • Volume : 19
  • No :5
  • Pages :212-222
  • Received Date : 2025-09-17
  • Revised Date : 2025-09-26
  • Accepted Date : 2025-10-16
  • DOI :https://doi.org/10.22696/jkiaebs.20250019
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